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library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: finetuning-sentiment-model-distil-samples
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetuning-sentiment-model-distil-samples
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3150
- Accuracy Percentage: 0.7514
- Accuracy Number: 133.0
- F1: 0.7460
- Precision: 0.7514
- Recall: 0.7514
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Percentage | Accuracy Number | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:---------------:|:------:|:---------:|:------:|
| 0.2349 | 1.0 | 22 | 0.6664 | 0.7571 | 134.0 | 0.7552 | 0.7571 | 0.7571 |
| 0.0531 | 2.0 | 44 | 1.0491 | 0.7232 | 128.0 | 0.7093 | 0.7232 | 0.7232 |
| 0.0374 | 3.0 | 66 | 1.1389 | 0.7119 | 126.0 | 0.7154 | 0.7119 | 0.7119 |
| 0.023 | 4.0 | 88 | 1.2514 | 0.7401 | 131.0 | 0.7288 | 0.7401 | 0.7401 |
| 0.0188 | 5.0 | 110 | 1.2064 | 0.7401 | 131.0 | 0.7355 | 0.7401 | 0.7401 |
| 0.0171 | 6.0 | 132 | 1.3531 | 0.7458 | 132.0 | 0.7365 | 0.7458 | 0.7458 |
| 0.0188 | 7.0 | 154 | 1.3221 | 0.7627 | 135.0 | 0.7534 | 0.7627 | 0.7627 |
| 0.0162 | 8.0 | 176 | 1.2874 | 0.7571 | 134.0 | 0.7507 | 0.7571 | 0.7571 |
| 0.018 | 9.0 | 198 | 1.2882 | 0.7627 | 135.0 | 0.7579 | 0.7627 | 0.7627 |
| 0.0097 | 10.0 | 220 | 1.3150 | 0.7514 | 133.0 | 0.7460 | 0.7514 | 0.7514 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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